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Research Papers: Design Automation

Topology Generation for Hybrid Electric Vehicle Architecture Design

[+] Author and Article Information
Alparslan Emrah Bayrak

Mechanical Engineering,
University of Michigan,
Ann Arbor, MI 48109
e-mail: bayrak@umich.edu

Yi Ren

Mechanical Engineering,
Arizona State University,
Tempe, AZ 85287
e-mail: yiren@asu.edu

Panos Y. Papalambros

Mechanical Engineering,
University of Michigan,
Ann Arbor, MI 48109
e-mail: pyp@umich.edu

1Corresponding author.

Contributed by the Design Automation Committee of ASME for publication in the JOURNAL OF MECHANICAL DESIGN. Manuscript received December 5, 2015; final manuscript received May 11, 2016; published online June 13, 2016. Assoc. Editor: Massimiliano Gobbi.

J. Mech. Des 138(8), 081401 (Jun 13, 2016) (9 pages) Paper No: MD-15-1800; doi: 10.1115/1.4033656 History: Received December 05, 2015; Revised May 11, 2016

Existing hybrid powertrain architectures, i.e., the connections from engine and motors to the vehicle output shaft, are designed for particular vehicle applications, e.g., passenger cars or city buses, to achieve good fuel economy. For effective electrification of new applications (e.g., heavy-duty trucks or racing cars), new architectures may need to be identified to accommodate the particular vehicle specifications and drive cycles. The exploration of feasible architectures is combinatorial in nature and is conventionally based on human intuition. We propose a mathematically rigorous algorithm to enumerate all feasible powertrain architectures, therefore enabling automated optimal powertrain design. The proposed method is general enough to account for single and multimode architectures as well as different number of planetary gears (PGs) and powertrain components. We demonstrate through case studies that our method can generate the complete sets of feasible designs, including the ones available in the market and in patents.

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References

Figures

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Fig. 1

Lever representation of three modes of a modified Chevrolet Volt architecture (without series hybrid mode): (a) hybrid configuration, (b) first pure electric configuration, (c) second pure electric configuration, and (d) combined multimode architecture

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Fig. 2

Representation of the hybrid configuration of the Chevrolet Volt architecture inFig. 1(a): (a) original bond graph representation of the hybrid configuration of the Chevrolet Volt architecture and (b) modified bond graph representation of the hybrid configuration of the Chevrolet Volt architecture

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Fig. 3

Example of a modified bond graph representation and its connectivity table

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Fig. 4

Configuration generation process flow

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Fig. 5

A junction with five bonds is equivalently replaced by three junctions with three bonds each

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Fig. 6

Two replicates generated from the enumeration process. Both graphs result in the same equation sets after assigning the junction type and bond weights.

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Fig. 7

All possible six combinations for the bond weight assignment around a 0-junction

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Fig. 8

Bond weight scaling for a 0-to-0 junction connection

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Fig. 9

Three sample connectivity tables and the corresponding clutching solution indicated by dashed boxes

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Fig. 10

All the modes of the dual-mode architecture by Ai and Anderson [23]: (a) first hybrid configuration and (b) second hybrid configuration

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Fig. 11

All the modes of the dual-mode architecture by Holmes et al. [22]: (a) first hybrid configuration and (b) second hybrid configuration

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